Python:从matplotlib.pyplot.contour()中找到等值线

I'm trying to find (but not draw!) contour lines for some data:

我试图找到(但不画!)一些数据的等高线:

from pprint import pprint 
import matplotlib.pyplot 
z = [[0.350087, 0.0590954, 0.002165], [0.144522, 0.885409, 0.378515], 
     [0.027956, 0.777996, 0.602663], [0.138367, 0.182499, 0.460879], 
     [0.357434, 0.297271, 0.587715]] 
cn = matplotlib.pyplot.contour(z) 

I know cn contains the contour lines I want, but I can't seem to get to them. I've tried several things:

我知道cn包含了我想要的等高线，但我似乎无法找到它们。我试了几件事情:

print dir(cn) 
pprint(cn.collections[0]) 
print dir(cn.collections[0]) 
pprint(cn.collections[0].figure) 
print dir(cn.collections[0].figure) 

to no avail. I know cn is a ContourSet, and cn.collections is an array of LineCollections. I would think a LineCollection is an array of line segments, but I can't figure out how to extract those segments.

都无济于事。我知道cn是一个ContourSet，和cn。集合是一系列的linecoll。我认为LineCollection是一系列的线段，但我不知道如何提取这些线段。

My ultimate goal is to create a KML file that plots data on a world map, and the contours for that data as well.

我的最终目标是创建一个KML文件，在世界地图上绘制数据，以及数据的轮廓。

However, since some of my data points are close together, and others are far away, I need the actual polygons (linestrings) that make up the contours, not just a rasterized image of the contours.

然而，由于我的一些数据点是紧密相连的，而另一些距离很远，我需要实际的多边形(linestrings)来组成轮廓，而不仅仅是轮廓的栅格化图像。

I'm somewhat surprised qhull doesn't do something like this.

我有点惊讶qhull不会做这样的事情。

Using Mathematica's ListContourPlot and then exporting as SVG works, but I want to use something open source.

使用Mathematica的ListContourPlot，然后导出为SVG，但我想使用一些开放源代码。

I can't use the well-known CONREC algorithm because my data isn't on a mesh (there aren't always multiple y values for a given x value, and vice versa).

我不能使用众所周知的CONREC算法，因为我的数据并不在网格上(给定的x值不总是有多个y值，反之亦然)。

The solution doesn't have to python, but does have to be open source and runnable on Linux.

解决方案不需要python，但必须是Linux上的开源和可运行的。

2 个解决方案

#1

You can get the vertices back by looping over collections and paths and using the iter_segments() method of matplotlib.path.Path.

您可以通过循环遍历集合和路径并使用matplotlib.path.Path的iter_分段()方法来获得顶点。

Here's a function that returns the vertices as a set of nested lists of contour lines, contour sections and arrays of x,y vertices:

这是一个返回顶点的函数，它是一组嵌套的等高线、等高线和x的数组，y顶点:

import numpy as np

def get_contour_verts(cn):
    contours = []
    # for each contour line
    for cc in cn.collections:
        paths = []
        # for each separate section of the contour line
        for pp in cc.get_paths():
            xy = []
            # for each segment of that section
            for vv in pp.iter_segments():
                xy.append(vv[0])
            paths.append(np.vstack(xy))
        contours.append(paths)

    return contours

---

Edit:

It's also possible to compute the contours without plotting anything using the undocumented matplotlib._cntr C module:

也可以不使用无文档的matplotlib来计算等值线。_cntr C模块:

from matplotlib import pyplot as plt
from matplotlib import _cntr as cntr

z = np.array([[0.350087, 0.0590954, 0.002165],
              [0.144522,  0.885409, 0.378515],
              [0.027956,  0.777996, 0.602663],
              [0.138367,  0.182499, 0.460879], 
              [0.357434,  0.297271, 0.587715]])

x, y = np.mgrid[:z.shape[0], :z.shape[1]]
c = cntr.Cntr(x, y, z)

# trace a contour at z == 0.5
res = c.trace(0.5)

# result is a list of arrays of vertices and path codes
# (see docs for matplotlib.path.Path)
nseg = len(res) // 2
segments, codes = res[:nseg], res[nseg:]

fig, ax = plt.subplots(1, 1)
img = ax.imshow(z.T, origin='lower')
plt.colorbar(img)
ax.hold(True)
p = plt.Polygon(segments[0], fill=False, color='w')
ax.add_artist(p)
plt.show()

#2

It seems that the contour data is in the .allsegs attribute of the QuadContourSet object returned by the plt.contour() function.

轮廓数据似乎是由plt.contour()函数返回的QuadContourSet对象的.allsegs属性。

The .allseg attribute is a list of all the levels (which can be specified when calling plt.contour(X,Y,Z,V). For each level you get a list of numpy nx2 arrays.

allseg属性是所有级别的列表(可以在调用plt.contour(X,Y,Z,V)时指定。对于每个级别，您将得到一个numpy nx2数组的列表。

plt.figure()
plt.contour(X, Y, Z, [0], colors='r')

plt.figure()
for ii, seg in enumerate(C.allsegs[0]):
    plt.plot(seg[:,0], seg[:,1], '.-', label=ii)
plt.legend(fontsize=9, loc='best')

In the above example, only one level is given, so len(C.allsegs) =1. You get:

在上面的示例中，只给出了一个级别，所以len(C.allsegs) =1。你会得到:

contour plot

等高线图

the extracted curves

提取的曲线